Smart Sustainable Manufacturing Systems

With the advent of disruptive digital technologies, companies are facing unprecedented challenges and opportunities. Advanced manufacturing systems are of paramount importance in making key enabling technologies and new products more competitive, affordable, and accessible, as well as for fostering their economic and social impact. The manufacturing industry also serves as an innovator for sustainability since automation coupled with advanced manufacturing technologies have helped manufacturing practices transition into the circular economy. To that end, this Special Issue of the journal Applied Sciences, devoted to the broad field of Smart Sustainable Manufacturing Systems, explores recent research into the concepts, methods, tools, and applications for smart sustainable manufacturing, in order to advance and promote the development of modern and intelligent manufacturing systems. In light of the above, this Special Issue is a collection of the latest research on relevant topics and addresses the current challenging issues associated with the introduction of smart sustainable manufacturing systems. Various topics have been addressed in this Special Issue, which focuses on the design of sustainable production systems and factories; industrial big data analytics and cyberphysical systems; intelligent maintenance approaches and technologies for increased operating life of production systems; zero-defect manufacturing strategies, tools and methods towards online production management; and connected smart factories

Advances in Manufacturing, Production Management and Process Control: Joint proceedings of the AHFE 2018 International Conference on Advanced Production Management and Process Control, the AHFE International Conference on Human Aspects of Advanced Manufacturing, and the AHFE International Conference on Additive Manufacturing, Modeling Systems and 3D Prototyping, July 21-25, 2018, Loews Sapphire Falls Resort at Universal Studios, Orlando, Florida, USA

This book discusses the latest advances in manufacturing and process control, with a special emphasis on digital manufacturing and intelligent technologies for manufacturing and industrial processes control. The human aspect of the developed technologies and products, their interaction with the users, as well as sustainability issues, are covered in detail. Development of new products using 3D printers, rapid prototyping systems, remote fabrication, and other advanced techniques, is described in detail, highlighting the state-of-the-art and current challenges. Other key topics include digital modeling systems and additive manufacturing, together with their applications in a number of fields, e.g in bioengineering/biomedicine, in the aerospace, maritime and military fields or for archeological and historical purposes, such as preserving structures, but not limited to this. The book is based on three AHFE 2018 affiliated conferences i.e. the AHFE 2018 International Conference on Advanced Production Management and Process Control, the AHFE 2018 International Conference on Human Aspects of Advanced Manufacturing, and the AHFE 2018 International Conference on Additive Manufacturing, Modeling Systems and 3D Prototyping, which were held on July 21-25, 2018, in Orlando, Florida, USA

Smart Monitoring of Manufacturing Systems for Automated Decision-Making: A Multi-Method Framework

Smart monitoring plays a principal role in the intelligent automation of manufacturing systems. Advanced data collection technologies, like sensors, have been widely used to facilitate real-time data collection. Computationally efficient analysis of the operating systems, however, remains relatively underdeveloped and requires more attention. Inspired by the capabilities of signal analysis and information visualization, this study proposes a multi-method framework for the smart monitoring of manufacturing systems and intelligent decision-making. The proposed framework uses the machine signals collected by noninvasive sensors for processing. For this purpose, the signals are filtered and classified to facilitate the realization of the operational status and performance measures to advise the appropriate course of managerial actions considering the detected anomalies. Numerical experiments based on real data are used to show the practicability of the developed monitoring framework. Results are supportive of the accuracy of the method. Applications of the developed approach are worthwhile research topics to research in other manufacturing environments

Collaborative Networks, Decision Systems, Web Applications and Services for Supporting Engineering and Production Management

This book focused on fundamental and applied research on collaborative and intelligent networks and decision systems and services for supporting engineering and production management, along with other kinds of problems and services. The development and application of innovative collaborative approaches and systems are of primer importance currently, in Industry 4.0. Special attention is given to flexible and cyber-physical systems, and advanced design, manufacturing and management, based on artificial intelligence approaches and practices, among others, including social systems and services

Evolution of maintenance strategies in oil and gas industries: the present achievements and future trends

Engineering Systems maintenance and reliability challenges have drawn serious attention of researchers and industrialists all over the world due to continuous evolution, innovation and complexity of modern technologies deployed in manufacturing and production systems. These systems need very high reliability and availability due to business, mission and safety critical nature of their operations. This paper reviews evolution of systems or equipment maintenance strategies practiced over the years in complex industrial and manufacturing systems such as oil and gas production systems, satellite communication system, spacecraft navigational system, nuclear power plants, etc. The paper also examines the current maintenance and reliability philosophies, their limitations and highlights major breakthroughs and achievements with regards to complex engineering systems maintenance. Intelligent maintenance, a novel approach to complex engineering systems maintenance and reliability sustainment is proposed. The proposed approach reintegrates operation and maintenance phase into system development life cycle, adopts advanced engineering tools and methodology in developing condition-based predictive maintenance, an intelligent maintenance system with resilient, autonomous and adaptive capabilities. Application of Neural network approach to multisensor data fusion for condition-based predictive maintenance system is briefly presented

Industry 4.0-Oriented Turnkey Project: Rapid Configuration and Intelligent Operation of Manufacturing Systems

More extensive personalized product requirements and shorter product life cycles have put forward higher requirements for the rapid establishment, commissioning, and operation of corresponding manufacturing systems. However, the traditional manufacturing system development process is complicated, resulting in a longer delivery time. Many manufacturing enterprises, especially small and micro enterprises, may not have the necessary manufacturing knowledge or capabilities to meet these requirements. Therefore, it is essential to promote the construction of turnkey projects under the paradigm of Industry 4.0, parallelizing and integrating the existing manufacturing system development process based on mass manufacturing equipment to quickly provide turnkey solutions for manufacturing systems’ configuration and implementation for these enterprises. This paper aims to extract and refine the configuration and operation key views of the Industry 4.0-oriented Turnkey Project (I4TP) from Reference Architecture Model Industrie 4.0 (RAMI4.0) and use it to guide the development of key functional processes of turnkey projects to achieve rapid configuration and efficient operation management of manufacturing systems. The turnkey project platform in the Advanced Manufacturing Technology Center (AMTC) is taken as a demonstration case to provide a reference idea for the rapid configuration and intelligent operation of the turnkey manufacturing system

Adapting Disruptive Applications in Managing Quality Control Systems in Intelligence Manufacturing

Controlling quality has become a major trend in the circle of manufacturers and production managers that engage in intelligent manufacturing all over the world, on account of industry 4.0, in recent times. Intelligent manufacturing therefore is the use of advanced applications, analytics, sensors and Internet of Things (IoT) to improve manufacturing. The aim of the study is to carry out a study on application of disruptive application in managing quality system in intelligent manufacturing with a view to improving manufacturing process in organizations. Survey methods was used in collating responses from production managers of manufacturing companies at selected locations censoring production managers and supervisors on some parameters such as areas of disruptions in the quality assurance monitoring and calibration in production process, issues and challenges involved in quality control systems in manufacturing, Man-Whitney U Test, T-test, Pearson’s Test were used to analyze the collated data. Also, this study presents advanced analytical tools and applications to improve quality in manufacturing process. The study finally presents areas of disruptions in the quality assurance monitoring and calibration in production process, issues and challenges involved in quality control systems in manufacturing, emerging areas of application and recommendation for improvement

Adapting Disruptive Applications in Managing Quality Control Systems in Intelligence Manufacturing

Controlling quality has become a major trend in the circle of manufacturers and production managers that engage in intelligent manufacturing all over the world, on account of industry 4.0, in recent times. Intelligent manufacturing therefore is the use of advanced applications, analytics, sensors and Internet of Things (IoT) to improve manufacturing. The aim of the study is to carry out a study on application of disruptive application in managing quality system in intelligent manufacturing with a view to improving manufacturing process in organizations. Survey methods was used in collating responses from production managers of manufacturing companies at selected locations censoring production managers and supervisors on some parameters such as areas of disruptions in the quality assurance monitoring and calibration in production process, issues and challenges involved in quality control systems in manufacturing, Man-Whitney U Test, T-test, Pearson’s Test were used to analyze the collated data. Also, this study presents advanced analytical tools and applications to improve quality in manufacturing process. The study finally presents areas of disruptions in the quality assurance monitoring and calibration in production process, issues and challenges involved in quality control systems in manufacturing, emerging areas of application and recommendation for improvement

Expanding the Horizons of Manufacturing: Towards Wide Integration, Smart Systems and Tools

This research topic aims at enterprise-wide modeling and optimization (EWMO) through the development and application of integrated modeling, simulation and optimization methodologies, and computer-aided tools for reliable and sustainable improvement opportunities within the entire manufacturing network (raw materials, production plants, distribution, retailers, and customers) and its components. This integrated approach incorporates information from the local primary control and supervisory modules into the scheduling/planning formulation. That makes it possible to dynamically react to incidents that occur in the network components at the appropriate decision-making level, requiring fewer resources, emitting less waste, and allowing for better responsiveness in changing market requirements and operational variations, reducing cost, waste, energy consumption and environmental impact, and increasing the benefits. More recently, the exploitation of new technology integration, such as through semantic models in formal knowledge models, allows for the capture and utilization of domain knowledge, human knowledge, and expert knowledge toward comprehensive intelligent management. Otherwise, the development of advanced technologies and tools, such as cyber-physical systems, the Internet of Things, the Industrial Internet of Things, Artificial Intelligence, Big Data, Cloud Computing, Blockchain, etc., have captured the attention of manufacturing enterprises toward intelligent manufacturing systems

Radio Frequency Identification (RFID) based wireless manufacturing systems, a review

Radio frequency identification (RFID) is one of the most promising technological innovations in order to track and trace products as well as material flow in manufacturing systems. High Frequency (HF) and Ultra High Frequency (UHF) RFID systems can track a wide range of products in the part production process via radio waves with level of accuracy and reliability.   As a result, quality and transparency of data across the supply chain can be accurately obtained in order to decrease time and cost of part production. Also, process planning and part production scheduling can be modified using the advanced RFID systems in part manufacturing process. Moreover, to decrease the cost of produced parts, material handling systems in the advanced assembly lines can be analyzed and developed by using the RFID. Smart storage systems can increase efficiency in part production systems by providing accurate information from the stored raw materials and products for the production planning systems. To increase efficiency of energy consumption in production processes, energy management systems can be developed by using the RFID-sensor networks. Therefore, smart factories and intelligent manufacturing systems as industry 4.0 can be introduced by using the developed RFID systems in order to provide new generation of part production systems. In this paper, a review of RFID based wireless manufacturing systems is presented and future research works are also suggested. It has been observed that the research filed can be moved forward by reviewing and analyzing recent achievements in the published papers